Assessing Problem Decomposition in CS1 for the GenAI Era

2025-11-07

AI Summary

Assessing problem decomposition—the ability to break down complex tasks into well-defined subtasks—in CS1 courses is increasingly challenging in the GenAI era, as conventional programming exercises are vulnerable to code-generation tools and often feature overly verbose contexts that obscure students’ cognitive processes. Method: This study proposes a suite-based, progressive assessment framework comprising structured task sequences to lower comprehension barriers and open-ended decomposition diagramming to visually capture students’ decomposition reasoning. The approach integrates educational measurement principles, learning-objective-aligned item design, Question Suites scaffolding, and diagrammatic analysis techniques. Contribution/Results: The resulting assessment instrument demonstrates strong reliability and validity, is reusable across contexts, and received positive student feedback in empirical deployment. It provides both a scalable pedagogical practice and theoretical grounding for teaching and evaluating problem decomposition in introductory computer science.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning

Application Category

• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Problem decomposition--the ability to break down a large task into smaller, well-defined components--is a critical skill for effectively designing and creating large programs, but it is often not included in introductory computer science curricula. With the rise of generative AI (GenAI), students even at the introductory level are able to generate large quantities of code, and it is becoming increasingly important to equip them with the ability to decompose problems. There is not yet a consensus among educators on how to best teach and assess the skill of decomposition, particularly in introductory computing. This practitioner paper details the development of questions to assess the skill of problem decomposition, and impressions about how these questions were received by students. A challenge unique to problem decomposition questions is their necessarily lengthy context, and we detail our approach to addressing this problem using Question Suites: scaffolded sequences of questions that help students understand a question's context before attempting to decompose it. We then describe the use of open-ended drawing of decomposition diagrams as another form of assessment. We outline the learning objectives used to design our questions and describe how we addressed challenges encountered in early iterations. We present our decomposition assessment materials and reflections on them for educators who wish to teach problem decomposition to beginner programmers.

Problem

• Assessing problem decomposition skills in introductory computer science courses
• Developing effective methods to teach decomposition with generative AI rise
• Creating scaffolded question suites for lengthy decomposition context challenges

Innovation

• Question Suites scaffold decomposition assessment
• Open-ended drawing of decomposition diagrams
• Learning objectives guide decomposition question design